mgserving

mgserving is a software component used in distributed systems for managing and serving machine learning models. It acts as an intermediary, allowing machine learning models to be deployed and accessed efficiently over a network. Typically, mgserving handles tasks such as model loading, inference execution, and communication with client applications.

The primary function of mgserving is to provide a standardized interface for interacting with machine learning models. This allows developers to deploy models written in various frameworks and languages without requiring clients to have direct knowledge of the underlying model implementation. By abstracting the complexities of model deployment, mgserving simplifies the process of integrating machine learning capabilities into larger applications.

Key features often found in mgserving solutions include support for different model formats, scalability to handle varying loads, and mechanisms for version management of deployed models. It can also incorporate features like batching requests to optimize inference throughput and monitoring capabilities to track performance and resource utilization. The goal is to make the deployment and operationalization of machine learning models more robust and manageable.